Evidence map›Paper›PMID 42035036›Full record

ArticleBMC pediatrics2026

Clinical and laboratory profiles of acute central nervous system infections in a Chinese pediatric cohort: a five-year retrospective analysis.

Shuyun Wang, Peibin Hou, Yu Ma, Xin Lv, Wandong Hu, Qian Zeng, Lingdong Zhu

Abstract read
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Article in BMC pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Shuyun WangClinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, China.
Peibin HouShandong Center for Disease Control and Prevention, Jinan, China.
Yu MaDisease Prevention and Control Center of China Railway Jinan Group Co Ltd, Jinan, China.
Xin LvClinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, China.
Wandong HuDepartment of Pediatric Neurology, Children's Hospital Affiliated to Shandong University, Jinan, China.
Qian ZengClinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, China.
Lingdong ZhuClinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, China. zhulingdong_sduch@163.com.

Funding

Big Data Program of Jinan Municipal Health Commission No. 2023-YBD-2-16
6 · The paper itself

Abstract

backgroundAcute central nervous system (CNS) infections in children cause severe neurological morbidity, but early diagnosis and risk assessment remain challenging. This study aimed to characterize the clinical and laboratory features, pathogen spectrum, and risk factors for severe disease in a five-year pediatric cohort.

methodsWe retrospectively analyzed children diagnosed with acute CNS infections at the Shandong Regional Children’s Medical Center from January 2020 to December 2024. Clinical, laboratory, and outcome data were extracted from electronic medical records.

resultsAmong 422 enrolled children, 132 (31.3%) had clinically diagnosed bacterial and 290 (68.7%) nonbacterial CNS infections. Bacterial infections were associated with significantly younger age (median 0.22 vs. 4.02 years), longer hospitalization (23.5 vs. 13 days), and higher rates of systemic complications (all P < 0.001). To distinguish bacterial from nonbacterial CNS infections, ROC analysis demonstrated that CSF protein had excellent discriminative ability (AUC = 0.917), followed by serum albumin (AUC = 0.869) and CSF white blood cells (AUC = 0.837). CRP (AUC = 0.801) and PCT (AUC = 0.682) were also evaluated. A total of 175 children (41.5%) required pediatric intensive care unit (PICU) admission. In addition to impaired consciousness, multivariate analysis identified respiratory failure (aOR = 39.76), somnolence (aOR = 15.03), vomiting (aOR = 3.93), seizure (aOR = 2.53), pneumonia (aOR = 2.51), age (aOR = 1.09), and length of hospital stay (aOR = 1.02) as independent predictors of PICU admission (all P < 0.05). Pathogens were identified in 94 cases (54 bacterial and 40 viral). Among bacterial pathogens, Streptococcus pneumoniae (n=13) and Escherichia coli (n=10) predominated, with 68.5% (37/54) occurring in infants ≤1 year. mNGS detected pathogens missed by conventional culture and identified co-infections.

conclusionsIn addition to CSF analysis, CRP can help distinguish bacterial from nonbacterial CNS infections; serum albumin and total protein (~50% sensitivity) can also help but should not be used alone. Impaired consciousness, respiratory failure, somnolence, vomiting, seizure, and pneumonia were key risk factors for PICU admission.The relatively high rate of bacterial infections in infants warrants particular clinical attention. These findings can guide clinical practice and improve outcomes in this vulnerable population.

Indexed as

Central Nervous System InfectionsAcute DiseaseChildChild, PreschoolChinaEast Asian PeopleFemaleHumansInfantMaleRetrospective StudiesRisk FactorsBacterial CNS infectionsCentral nervous system infectionsChildrenNonbacterial CNS infectionsPathogenPediatric intensive care unitRetrospective analysis

Identifiers

PMID42035036
PMCPMC13248359

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